Quiet and Effective: Value in HR Technology

The hot stuff in HR technology these days is all to do with social networking. Recruiters are flocking to social media with the energy of a bull let loose in a pasture full of lonely cows during mating season. All that effort does produce some results — candidates (or calves; depending on what you’re thinking right now) — but they’re inconsistent (in both cases). And there are plenty of skeptics that question the value of social networking as a scalable recruiting solution. Social media has its place in the recruiting universe, but the buzz around it is overshadowing other interesting technologies. Two in particular that I’d like to highlight may not be as exciting, but address fundamental needs for recruiters.

Effective Matching

The first is QuietAgent. It has developed a new approach to matching candidates and jobs. Matching technology is nothing new. Other products have been available for at least a decade. But most matching products are a black box. Using them requires having total faith in the methodology and algorithms developed by the vendors. They do work, but frequently it’s not all clear why candidates get ranked in a particular way. There’s also no way for a recruiter to influence the matching. The vendors are not inclined to let anyone do so because the technology is the result of a big investment in research. Recruiters find this “father-knows-best” approach frustrating when the matching doesn’t produce the kind of results they expect.

QuietAgent has moved beyond these limitations. The technology uses the ONet database as the basis for classifying and matching jobs with resumes. ONet is the largest occupational classification system in the world, and it’s in the public domain, making the basis for matches better understood. More importantly, QuietAgent’s technology can be adapted. Users can adjust how the matching works. A user can specify different combinations of criteria on which to match candidates with jobs. For example, five years of experience and certain skills, or three years and a different set. This is a big deal, as all recruiters know. Hiring criteria are rarely rigid, and search tools, such as the ones on job boards and ATS, allow for little flexibility.

QuietAgent is the technology behind AllianceQ and UnitedWeWork. The former is an association of larger employers that are willing to share resumes of candidates with others. The latter is a free job board. QuietAgent’s association with AllianceQ makes for a powerful combination, because it also provides a supply of candidates. This may not seem like much today, when candidates are in abundance, but the day will come when candidates are again in short supply; then, this makes for a great combination in one package.

Reliable Resumes

I recently heard an interview with a NASA veteran who was hired at the start of the Apollo program. What was most interesting was that he and most other engineers were hired at NASA purely on the basis of their resumes. They sent in a resume and subsequently received an offer letter. This wasn’t unusual, up until the 1960s. Bringing candidates in from out of town was rarely done because of the expense. And no one did phone interviews; long distance calls cost a lot, and the sound quality wasn’t all that great. If a candidate looked good on paper then they were often hired.

How things change. A resume isn’t worth a whole lot today. We use it as the starting point of a long process. That is the way it needs to be. By some estimates a third or more contain significant exaggerations or outright lies.

One company solving this problem is Resumefit. Candidates who complete the company’s assessments get a “certified resume” locked with a digital key. The value here is that any recruiter receiving the resume can be assured that the claimed skills are true. Other vendors have attempted to create equivalent products before, but they’ve focused more on verifying employment, references, and criminal history. That has limited value before a hiring decision is made. Knowing that the skills and abilities described meet a certain level is much more useful to employers using skills-based hiring. This makes the recruiting process much more efficient because recruiters don’t have to waste time trying to read between the lines and can be reasonably assured that decisions they make are based on reliable information.

QuietAgent and Resumefit may not generate the buzz created by Twitter but they are solutions to well-known problems and serve very fundamental needs in recruiting. These needs will still be around when the ardor for social networking cools, as it will. Recruiters use of social media will balance out once its usefulness is better understood, settling into a niche supporting referrals and talent communities. But we’ll still be looking for effective and efficient ways to match candidates with jobs and find resumes with reliable information.

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About the Author

Raghav Singh is director of product management at PeopleFluent. He has previously been in product management and marketing roles at several HR technology vendors. His career has included work as a consultant on enterprise HR systems and as a recruiting and HRIT leader at several Fortune 500 companies.

Raghav your cognitive style always makes me smile: you seem to do a lot of reasoning using the lens of the contra-position, which by its nature serves up lots of softballs for pedantic beadles such as myself.

Right off the bat, your item is titled “quiet and effective” but instant irony: it’s illustrated by a Saturn V rocket at full rip: one of the loudest devices ever made. (I grant the Saturn V was effective!)

In this case, you are dead right on the case against most AI search systems for resumes. They are great for demos and they wow the inexperienced, but they don’t do jack for getting better actionable results out of a database.

I am all for a real-time parse of a document (i.e. once you find a resume, you can use a filter view to sort possible skills, dates of employment, employers, etc.) but a one time pass using a black box criteria just does not get it done- the data is unstructured so adding known structure to your query collection is a must.

QuietAgent seems to have a way better approach and that is notable. Resumefit on the other hand, I’m not sure about. It seems that some of Teh Doubt just shifts to the efficacy of that product and away from the candidate, and I don’t know how that saves time or money….joins a huge list of assessment tools some great, some less than worthless…..

Todd Raphael

He’s innocent when it comes to the rocket irony. I added it in because it was an Apollo rocket, and he talked about Apollo. And I thought it kind of fit, since he talked about the powerful nature of these applications. But yeah, it may not have been so quiet.

Martin Snyder

Ha- I knew Raghav did not do the layout but I hate to miss a chance like that 😉

The loudest object ever ? Probably the Tsara Bomba.

I’m not sure current hiring practices are much better considering how well Apollo performed, although we got lucky a few times to not lose crews.. 13 of course but others too…

Raghav Singh

I suppose a picture of a Prius might have been better, but that’s not as interesting.

Actually, the choice of the Saturn V rocket is appropriate in another way. That’s essentially what a lot of matching products represent – big and expensive. They work but at a high cost. Quietagent has made the technology much more accessible.

Keith Halperin

I suspect that Behavioral Recruiting (the application of Behavioral Economics to Recruiting) will show the use of resumes in hiring to be a far more subjective and imprecise tool than is normally considered. It would be interesting to develop an elegant and robust non-resume-based hiring process based on asking applicants a series of relevant questions without initial human intervention. This would require a much more formalized and standardized approach to job descriptions than currently exists- the use of ONet suggests a small step in this direction.

However, I do not expect much progress in the development and adoption of these and other methods which I refer to as Generally Accepted Recruiting (or Hiring) Practices: GARP (or GAHP)- there is too much money to be made under the current disorganized, inefficient status quo. As it is said: “In the Country of the Blind, the One-Eyed Man is king.”

What I like about O*Net Keith, is that is it a great start, and realistically, who is going to spend $50 million a year to build and maintain another comparative network like the US DOL does?

O*Net may not be perfect, but it is a standard that lets both parties (job seekers and employers) speak the same language – and that greatly increases the chances of both parties getting what they want – and a whole lot faster.

We convinced the country of New Zealand to move away from its own job classification system and go to O*Net as a standard for their entire workforce system. The rationale was two-fold, 1) that in order to reduce unemployment you had to provide a way employers could easily participate in workforce, and that meant getting everyone to ‘speak’ the same language (difficult as government’s typically love arcane anachronisms!), and 2) (and this is the wining key in my book), O*Net focuses on working styles and tasks (which are globally relevant). By doing this they say: “If we can find someone who likes laying bricks in Bosnia (the working style, activities, etc of laying bricks), they going to like laying bricks in Boston.” Finding people (in part) based on their interest / willingness to perform in the way we are going to ask them to perform in a role, leads to retention – someone who likes doing the kinds of things we ask, is more likely to be better at it and stay longer – Retention is one key element in fixing unemployment.

What else I really like about O*Net is that the way in which O*Net breaks down each job into a set of skills, competencies, tasks, working styles and interests. This is key in my mind, because it allows vendors to solicit a single set of information from candidates (skills, competencies, tasks, working styles and interests ) to build a resume (more correctly a career profile), rather that forcing a candidate to understand what information is important for the employer to know about them. This then means that a single candidate career profile can be broken down into the individual parts and built back-up (matched) against any job using the same basis for measurement / evaluation. This is key is adaptive selection, as it allows us to identify and move talent. When you then allow recruiters to establish a job requirement using those same elements, well you get the picture – no matter what they do they get quality matches as candidates are measured to the underlying elements of their career profile in the ‘same language’.

Breaking down a candidate and a job to a set of common elements such as O*Net provides, is key to leveling the playing field and truly providing a globally accessible and scalable employment selection system. In this economy where we (currently) have an abundance of underemployed (as opposed to unemployed) talent, we need tools enabling that talent to be found or find career opportunities that make use of the skills, competencies, tasks, working styles and interests they possess, and not necessarily “just what they have done before” – this “talent movement” requirement can only be realistically achieved when a standard is followed.

Weather you believe O*Net to be comprehensive enough or absolutely correct (may) become somewhat a moot point. O*Net (in the way QuietAgent have implemented around it at least), or any standard for that matter, forces both sides into a transparent and truthful representation of what they have to offer, as it solicits common elements of data regardless of the end users bias / view of value. This gives us all kinds of benefits from identifying transferrable skills, providing career path / expectation alignment, creating and identifying talent for new economy jobs, to providing ways for people without work experience to compete with those that do.
In my view, none of this is possible with the old boys club of ‘eyeballs’, web traffic, job advertising and two dumb documents trying to find each other! (resume-to-job descriptions).

Yet to be seen if we are right of course, but logic tells me O*Net is moving along the right path.

Raghav,
Well said regarding most matching applications – same goes to Martin (I loved this – AI matching apps “…are great for demos and they wow the inexperienced, but they don’t do jack for getting better actionable results out of a database.”).

Eiji Toyoda, the fifth president of Toyota Motor Corporation, who collaborated Taiichi Ohno to fine tune the concept of Kaizen as well as to develop the core concepts of the ‘Toyota Way’, explains brilliantly: “Society has reached the point where one can push a button and be immediately deluged with…information. This is all very convenient, of course, but if one is not careful there is a danger of losing the ability to think. We must remember that in the end it is the individual human being who must solve the problems.”

As I have written before, thinking is the most critical step in the candidate sourcing process, and regardless of “Artificial Intelligence” and semantic search marketing hype, applications do not have any true cognitive power, nor do they have the ability to be creative or learn as people do. Thus I could not agree more with Jeffrey Liker’s (author of The Toyota Way) assessment – “People do the work, computers move information.”

You should check out Radar Hybrid ATS from Goaltender Solutions. Job profiles, job matching based on O*NET.. other assessments as well. Including a new Tenure survey. The only full-function ATS with a robust suite of assessments included.

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ERE serves corporate recruiters and talent acquisition professionals by providing news and insights about the recruiting industry, opinions on what's hot in the talent acquisition space, and evaluations on the best technology for recruiting.